Home Digital Marketing Digital Advertising Benchmarks 2020. How Do You Stack Up?
Digital Marketing - July 11, 2020

Digital Advertising Benchmarks 2020. How Do You Stack Up?

I’ve been asked continuously over the last twenty years “what’s a good click through rate, bounce rate, time on site, etc.” and more recently, “what’s a good IVT (invalid traffic) rate?” My answer has always been that industry wide digital advertising benchmarks are meaningless because they are not actionable, even though it is very tempting to compare yourself to them. Let me explain why. 

Comparing Apples to Cherries

Let’s take simple things like bounce rates, time on site, and number of pages per session; all of these are readily available in Google Analytics. A “good” bounce rate, time on site, and number of pages per session is entirely different depending on the nature of the site or the industry vertical to which it belongs. For example, for a medical journal site, doctors come to read one article to get answers they need at that moment; and then they leave. The number of pages for that sesion may be one page and the time on site relatively low, because they found their answer and left. For a travel booking site, the user may do a search for hotels and then click to check out a few of the search results. Their time on site might be much higher, and the number of pages also much higher. The user was doing research and trying to book a hotel; so they looked at dozens of pages. The benchmarks for a medical journal site are entirely different from those of a travel booking site. Any comparisons would be apples to cherries. And this is why industry wide benchmarks are meaningless and not applicable to your specific situation. 

Use Your Own Organic Traffic As Benchmark

Instead of comparing your analytics to industry wide benchmarks, look at their own organic traffic. I recommend you use those characteristics as the benchmarks for judging the efficacy of your paid digital marketing campaigns. Users who searched for something on Google and then clicked through on an organic search result probably wanted to be there. So the characteristics of time on site, bounce rate, and pages per session would serve as good benchmarks for what real, human visitors look like and do on your site. Do your paid marketing campaigns over-index, match, or under-index these benchmarks? If the paid marketing campaigns cannot deliver users that are at least comparable or better than your own organic traffic, then it may be wise to spend less on those campaigns. But if your paid campaigns deliver users to your site that bounce less, stay longer, and look at more pages, compared to your own organic benchmarks, then add budget to those campaigns so you will get more of the right kind of user to your site. 

What’s A Good Bot Benchmark? Zero, If Possible

When it comes to IVT and fraud, a good benchmark is zero fraud and bots. Of course, that’s not always possible. So it is important to measure for bots and take steps to reduce the invalid traffic. You can only do this if you knew how much of your traffic was bots and which bots they were. Google Analytics does not tell you this. FouAnalytics does. Bots are designated as follows: 1) dark red means malicious bots, 2) orange means declared bots – ones that say their name honestly in the user agent/browser name, and 3) yellow means search engine bots and crawlers. 

When we look at billions of pageviews over long periods of time (the chart below), and we see consistency like in the following #FouAnalytics chart, we can use this as a benchmark for what good publishers look like. There is a lot of dark blue — which means humans — and very little dark red (bots). There is some yellow, but that is desirable because publishers need search engine crawlers to index their sites. Note the amount of yellow remains low, over time. 

FouAnalytics chart on good publisher, on-site measurement

Good publishers don’t have rampant amounts of bots on their sites. This is because they have large human audiences, they don’t buy traffic, and fraud bots won’t waste their time causing pages to load on these sites because they don’t get paid. Fraud bots will load pages on long tail sites that pay them for traffic. The example above is just one good, mainstream publisher. Dozens and dozens more look similar to this. Note that we measure for humans (dark blue) in addition to measuring for bots. Other current fraud verification tech platforms only measure for IVT and give you a number. Those are useless because they are not actionable. You can’t do anything with just a percentage IVT number as many site owners have told me.  

On-Site Measurement vs In-Ad Measurement

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